This invention relates generally to computerized imaging systems and more particularly to methods and apparatus for processing data obtained from such imaging systems.
Two-dimensional (2D) filtered back-projection (FBP) reconstruction algorithms are efficient computationally and provide robust imaging performance. Thus, these algorithms are commonly used in CT imaging apparatus, even though CT has progressed from conventional fan beam (FB) scanners to state-of-the-art multi-detector-row scanner. Volumetric CT (VCT) scanners are among the most recent developments in CT imaging apparatus. In VCT scanners, three-dimensional (3D) or cone beam (CB) FBP reconstruction algorithms are used. One practical CB FBP reconstruction algorithm (FDK) has been described by Feldkamp et al. in “Practical cone-beam algorithm,” J. Opt. Soc. A., Vol. 1, pp. 612–619, 1984. The original FDK has been heuristically extended from its 2D FB counterpart to the CB case based upon a circular source trajectory, in which a one-dimensional (1D) row-wise ramp filtering and 3D back-projector are used. Subsequently, the FDK algorithm has been extended to handle the helical CB data acquisition geometry (namely helical FDK), in which a row-wise 1D ramp filtering is still used, as described by Wang et al. in “A general cone-beam reconstruction algorithm,” IEEE Trans. Med. Imag., vol. 12, pp. 486–496, 1993. In principal, the helical FDK algorithm is an approximate CB reconstruction algorithm, even though a helical source trajectory satisfies the so-called data sufficiency condition. The helical FDK can satisfactorily eliminate artifacts caused by cone beam angle due to the utilization of 3D back-projection under small to medium cone angle. However, the suppression of helical artifacts, such as streak, shading/glaring and geometric distortion caused by data inconsistencies in helical data acquisition, is not as satisfactory. To suppress helical artifacts, adequate helical view weighting strategies before filtering have to be exercised, as described by Crawford et al., “Computed tomography scanning with simultaneous patient translation,” Med. Phys. 17(6), pp. 967–982, 1990.
Exact helical CB reconstruction algorithms offer theoretically accurate CB reconstruction capability. However, exact helical CB reconstruction algorithms have various disadvantages that may include non-FBP computational structure; poor spatial resolution; poor noise characteristics; or poor computational efficiency.